109 citations · 636 across the 74 of their papers we have counts for
82 papers
Face Identity-Aware Disentanglement in StyleGAN
Adrian Suwała, Bartosz Wójcik, Magdalena Proszewska +3
Conditional GANs are frequently used for manipulating the attributes of face images, such as expression, hairstyle, pose, or age. Even though the state-of-the-art models successful…
Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations
Mikołaj Sacha, Bartosz Jura, Dawid Rymarczyk +3
Prototypical parts-based networks are becoming increasingly popular due to their faithful self-explanations. However, their similarity maps are calculated in the penultimate networ…
ChiENN: Embracing Molecular Chirality with Graph Neural Networks
Piotr Gaiński, Michał Koziarski, Jacek Tabor +1
Graph Neural Networks (GNNs) play a fundamental role in many deep learning problems, in particular in cheminformatics. However, typical GNNs cannot capture the concept of chirality…
Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training
Aleksandra I. Nowak, Bram Grooten, Decebal Constantin Mocanu +1
Dynamic Sparse Training (DST) is a rapidly evolving area of research that seeks to optimize the sparse initialization of a neural network by adapting its topology during training.…
ProMIL: Probabilistic Multiple Instance Learning for Medical Imaging
Łukasz Struski, Dawid Rymarczyk, Arkadiusz Lewicki +3
Multiple Instance Learning (MIL) is a weakly-supervised problem in which one label is assigned to the whole bag of instances. An important class of MIL models is instance-based, wh…
MultiPlaneNeRF: Neural Radiance Field with Non-Trainable Representation
Dominik Zimny, Artur Kasymov, Adam Kania +4
NeRF is a popular model that efficiently represents 3D objects from 2D images. However, vanilla NeRF has some important limitations. NeRF must be trained on each object separately.…